1. Field of the Invention
Generally, the invention involves a process for forming radar images. More specifically, the invention involves a process for detecting moving targets and for forming focused radar images of moving targets.
2. Description of the Related Art
Radar, at its most basic application, is used to measure the range to a target. With knowledge of the speed of propagation of the wave, i.e., electromagnetic wave, that is transmitted toward the target, it is possible to resolve in a first dimension, the distance to the target, based on the received reflected wave or echo. In order to use radar as an imaging tool, it is necessary to collect information about the cross-range of the target, in addition to the first dimension information. This cross-range information is about a second dimension perpendicular to the first dimension.
Synthetic aperture radar (SAR) can be used to collect data in both the first and second dimensions, through a process wherein the reflected waves are measured at different angles with respect to an object-of-interest. This process is referred to in the art as collecting radar measurements over a synthetic (as opposed to a literal) aperture. By taking various measurements of the object-of-interest from varying aspect angles, it is possible to determine approximate distance to the scattering centers within an object-of-interest in the first dimension and location of these scattering centers within the object-of-interest in the second, cross-range dimension. This process of two-dimensional imaging is commonly referred to as reflection tomography.
SAR systems take advantage of the long-range propagation characteristics of radar signals and the complex information processing capability of modern digital electronics to provide high-resolution imagery. SAR imaging is not restricted by time of day or atmospheric conditions due to its operative frequencies. Consequently, SAR imaging supplements other photographic and optical imaging techniques in order to facilitate environmental monitoring, earth-resource mapping, and military operations which may require broad-area imaging at high resolutions. More specifically, SAR technology provides detailed terrain information to geologists for mineral exploration, environmentalists for determination of oil spill boundaries, navigators for sea state and ice hazard mapping, and the military for reconnaissance and targeting information.
Other systems using reflection data, also referred to as projection measurements, are police radars for vehicle speed monitoring and detection, fault inspection systems using acoustic imaging, submarine sonar for imaging underwater objects and the like, seismic imaging system for tunnel detection, oil exploration, geological surveys, etc., and medical diagnostic tools such as sonograms and echocardiograms.
There have been two basic types of processing techniques used in the field of reflection tomography to reconstruct single-bounce (SB) reflection data. First, the frequency-domain projection-slice theorem takes the measured phase history from the reflection data taken at different aspect angles and generates the reconstruction of an image using Fourier transforms. This reconstruction technique is often used for reconstructing SAR image data in order to minimize the computational load that results from necessarily complex processing. A second technique, more prevalent in the medical imaging community, is based on the time-domain back projection techniques. Both of these techniques are discussed in U.S. Pat. No. 5,805,098 to McCorkle which is incorporated herein by reference in its entirety.
An image reconstruction algorithm designed to detect and extract multiple bounce scattering effects on image formation is described in U.S. patent application Ser. No. 10/954,218 entitled PROCESS FOR MAPPING MULTIPLE-BOUNCE GHOSTING ARTIFACTS FROM RADAR IMAGING DATA” filed Oct. 1, 2004 which is a continuation of U.S. patent application Ser. No. 10/631,712 entitled PROCESS FOR MAPPING MULTIPLE-BOUNCE GHOSTING ARTIFACTS FROM RADAR IMAGING DATA” which claims priority to U.S. Pat. No. 6,646,593 similarly titled, which claims priority to U.S. Provisional Patent Application No. 60/345,639, entitled “SPOTLIGHT SAR IMAGE FORMATION WITHOUT MULTIPLE-BOUNCE GHOSTING ARTIFACTS” filed Jan. 8, 2002, all of which are incorporated herein by reference in their entirety.
The reflection data processing techniques described in the related art described herein assume that the impinging wave reflects off of an object of interest that is stationary within the scene of interest before returning back to the receiver. This assumption neglects the situation wherein the wave actually reflects off of a target or object of interest that changes its location within the scene as the sensor is collecting the data used for image reconstruction.
In prior art directed at the task of detecting and imaging moving targets, Perry et al., “SAR Imaging of Moving Targets,” IEEE Aerospace and Electronic Systems, Vol. 35, No. 1, 1999, pp. 188-200, developed a technique for performing SAR imaging of moving targets based upon techniques that are similar to that of conventional moving target indication (MTI) techniques applied to SAR data. In particular, these authors argue that “standard techniques, such as CFAR (constant false alarm rate) detection prescreening may be used to isolate both the static and moving targets from the scene.” They further claim that “this is more difficult for the unfocused movers because they are smeared more than static targets and hence require a larger target-to-clutter ratio for good detection at reasonable false alarm rates.” Thus, these techniques effectively separate the moving targets from the stationary clutter prior to the processing used to actually focus well-formed images of the moving targets. Perry et al. claim “this approach does work, however, for sparse nonurban scenes” as exemplified by their good results for isolated vehicles on a desert road in China Lake, Calif. However, this prior art does not offer such claims of success in more challenging urban environments that typically have a much higher level of stationary clutter. They further claim that the use of “a zero-Doppler clutter filtering technique, such as DPCA (displaced phase center antenna)” can be used to improve the pre-detection of moving targets. However, DPCA requires the platform to have multiple radar antennas.
Other techniques for separating moving targets from SAR data, such as are described in Friedlander et al., “VSAR: A High Resolution Radar System for Detection of Moving Targets,” IEE Proceedings on Radar, Sonar, and Navigation, Vol. 144, No. 4, August 1997, pp. 205-218, are also known. However, these methods require that the platform possess multiple radar antennas.
Other prior art approaches that use conventional SAR data to estimate the locations and velocities of surface targets moving in an arbitrary direction are highly dependent on scene context and, furthermore, require a high level of human interaction to yield viable results. See Carrara et al. “Spotlight Synthetic Aperture Radar-Signal Processing Algorithms,” Artech House, Boston, 1995, pp. 238-241. In particular, the required contextual information is that of a road network. Through use of intensive human analysis and a good SAR simulation tool, it is possible to estimate target location and velocity based on the existence of a cross-range streak in conventional SAR imagery. These approaches use a trial-and-error approach wherein a human analyst performs the following steps: 1) modeling the forward problem, wherein scene context is used to make an initial hypothesis for the location and trajectory of a surface moving target within the scene; 2) using a SAR simulator to analyze the streak signature arising in a conventional SAR image due to the hypothesized moving target; 3) comparing the results of the simulation with the actual measured SAR image; 4) using this comparison to refine the hypothesis of the target location and trajectory; 5) iterating until the human analyst is satisfied with the correlation between the simulated streak signature and the that of the actual measured data; and 6) applying this procedure to the next candidate moving target in the original SAR image, as evidenced by the existence of a cross-range streak in the image. This approach is human-intensive and typically requires auxiliary road network information to yield correct estimates the locations and trajectories of surface moving targets using SAR data. However, such techniques often yield ambiguous results, as there are typically many different roads on which any particular target may be moving and which may give rise to identical signature streaks in the conventional SAR image. Furthermore, certain types of contextual information, e.g. road network information) may not be reliable for many tactical targets, e.g. tanks, because such vehicles are not typically constrained to travel on road networks.